Methods and systems for measuring sensor visibility
Provided are methods for methods and systems for measuring sensor visibility, which can include obtaining sensor data associated with an autonomous vehicle and determining a blockage parameter indicative of a blockage of a sensor based on a comparison of the sensor data with secondary data. Some methods described also include controlling an operation of an autonomous vehicle based on the blockage parameter. Systems and computer program products are also provided.
1 . A method, comprising:
obtaining, using at least one processor, first sensor data from a first sensor associated with a first autonomous vehicle, wherein the first sensor data is indicative of an environment in which the first autonomous vehicle is operating;
obtaining, using the at least one processor, environment data indicative of the environment;
determining, using the at least one processor, based on a comparison of the first sensor data and the environment data, a first blockage parameter indicative of a first blockage of the first sensor;
obtaining, using the at least one processor, a second blockage parameter from a second autonomous vehicle operating in the environment, wherein the second blockage parameter indicates a second blockage of a second sensor associated with the second autonomous vehicle, wherein the second autonomous vehicle determines the second blockage parameter;
determining, using the at least one processor, an adverse weather condition in the environment based on the first blockage parameter and the second blockage parameter;
controlling, based on the determined adverse weather condition, an operation of the first autonomous vehicle; and
communicating the determined adverse weather condition to a fleet management system, wherein the fleet management system is configured to updates driving parameters for a fleet of autonomous vehicles in the environment based on the determined adverse weather condition.
2 . The method of claim 1 , wherein determining the first blockage parameter comprises determining, using the at least one processor, whether the first sensor data satisfies a criterion.
3 . The method of claim 2 , wherein determining the first blockage parameter comprises, in response to determining that the first sensor data does not satisfy the criterion, determining, using the at least one processor, the first blockage parameter as indicative of the first sensor being blocked.
4 . The method of claim 3 , wherein the criterion is based on an object indicated by the environment data, wherein the first sensor data satisfies the criterion when the first sensor data indicates a presence of the object.
5 . The method of claim 1 , wherein the environment data is based on three-dimensional map data and data obtained from a third sensor associated with the first autonomous vehicle.
6 . The method of claim 5 , wherein the third sensor is a same type of sensor as the first sensor.
7 . The method of claim 5 , wherein the first sensor is a non-radar sensor and the third sensor is a radar sensor.
8 . The method of claim 5 , further comprising:
determining, by the at least one processor, based on the first sensor data and the environment data, an overlapping field-of-vision parameter indicative of a maximum overlapping field-of-vision of the first sensor and the third sensor.
9 . The method of claim 8 , wherein determining the first blockage parameter comprises determining, using the at least one processor, whether the first sensor data satisfies a criterion, wherein the criterion is based on the environment data and the overlapping field-of-vision parameter.
10 . The method of claim 1 , the method comprising obtaining, using the at least one processor, location data indicative of a location of the first autonomous vehicle.
11 . The method of claim 10 , wherein the comparison of the first sensor data and the environment data comprises a comparison of the first sensor data and a localized environment data, wherein the localized environment data is obtained based on the environment data and the location data.
12 . The method of claim 1 , wherein the first sensor is selected from a group consisting of a radar sensor, a camera sensor, and a LIDAR sensor.
13 . The method of claim 1 , wherein the operation comprises one or more of a speed, an acceleration, and a direction of the first autonomous vehicle.
14 . The method of claim 1 , wherein the fleet of autonomous vehicles comprises a plurality of autonomous vehicles, wherein to update the driving parameters the fleet management system is configured to update an operating route to avoid the environment.
15 . The method of claim 1 , further comprising decelerating the first autonomous vehicle.
16 . A non-transitory computer readable medium comprising instructions stored thereon that, when executed by at least one processor, cause the at least one processor to carry out operations comprising:
obtaining first sensor data from a first sensor associated with a first autonomous vehicle, wherein the first sensor data is indicative of an environment in which the first autonomous vehicle is operating;
obtaining environment data indicative of the environment;
determining based on a comparison of the first sensor data and the environment data, a first blockage parameter indicative of a first blockage of the first sensor;
obtaining, using the at least one processor, a second blockage parameter from a second autonomous vehicle operating in the environment, wherein the second blockage parameter indicates a second blockage of a second sensor associated with the second autonomous vehicle, wherein the second autonomous vehicle determines the second blockage parameter;
determining an adverse weather condition in the environment based on the first blockage parameter and the second blockage parameter;
controlling, based on the determined adverse weather condition, an operation of the first autonomous vehicle; and
communicating the determined adverse weather condition to a fleet management system, wherein the fleet management system is configured to update driving parameters for a fleet of autonomous vehicles in the environment based on the determined adverse weather condition.
17 . A system, comprising at least one processor; and at least one memory storing instructions thereon that, when executed by the at least one processor, cause the at least one processor to:
obtain first sensor data from a first sensor associated with a first autonomous vehicle, wherein the first sensor data is indicative of an environment in which the first autonomous vehicle is operating;
obtain environment data indicative of the environment;
determine, based on a comparison of the first sensor data and the environment data, a first blockage parameter indicative of a first blockage of the first sensor;
obtain a second blockage parameter from a second autonomous vehicle operating in the environment, wherein the second blockage parameter indicates a second blockage of a second sensor associated with the second autonomous vehicle, wherein the second autonomous vehicle determines the second blockage parameter;
determine an adverse weather condition in the environment based on the first blockage parameter and the second blockage parameter;
control, based on the determined adverse weather condition, an operation of the first autonomous vehicle; and
communicate the determined adverse weather condition to a fleet management system, wherein the fleet management system is configured to update driving parameters for a fleet of autonomous vehicles in the environment based on the determined adverse weather condition.
18 . The system of claim 17 , wherein the environment data includes three-dimensional map data and data obtained from a third sensor associated with the first autonomous vehicle.